code: def manifest_image_activations(model, image, **kwargs):
      start = timer()
      activations_dict = image_activations(model, image, **kwargs)
      end = timer()
      elapsed = end - start
  
      results = {"type": "image-activations", "took": elapsed}
  
      results["values"] = [
          {
              "type": "activations",
              "value": value,
              "shape": value.shape,
              "layer_name": layer_name,
          }
          for layer_name, value in activations_dict.items()
      ]
  
      return results
  
file_path: lucid/lucid/recipes/image_activations.py
imports: from timeit import default_timer
  import tensorflow
  from lucid.optvis import render
  from lucid.optvis import param
  from lucid.optvis import transform
  from lucid.optvis import objectives
  from lucid.optvis import overrides
  from lucid.misc.io import show, load
  from lucid.misc.ndimage_utils import resize
label_desc: Use image node_id 2 for calling a global function with example usage: manifest_image_activations(model, image) and returns: results